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1,605 records · Page 81Linked to original sources
USGS2024

Imaging of seismic discontinuities using an adjoint method

For imaging of seismic discontinuities at depth, reverse time migration (RTM) is a powerful method to apply to recordings of seismic events. It is especially powerful when an extensive receiver array, numerous seismic sources, or both, permit adequate reconstruction of incident and scattered wavefields at depth. Reconstructing either the incident or scattered wavefield at depth becomes less accurate when relatively few recordings of seismic events are available. Here we explore an inverse scattering approach to imaging discontinuities based on an adjoint method, employing sensitivity kernels (Frechet derivatives) that represent jumps in material properties across seismic-discontinuity surfaces. When combined with ray-based requirements on scattering geometry, it constitutes a powerful approach to determining the locations and amplitudes of the discontinuities, recovering only those properties that can be resolved by a spatially limited source and/or receiver distribution. This is illustrated by synthetic examples with local sources followed by a field example in a subduction zone setting

Washington↗
USGS2025

Site-specific, extended ShakeMaps for earthquake engineering applications

The U.S. Geological Survey (USGS) routinely produces ShakeMaps of shaking intensity across the globe. Due to practical constraints, the number of response spectral periods was limited to three standard periods (0.3, 1.0, and 3.0 sec). We have recently developed the tools that are necessary to expand this functionality to include 22 periods (matching the current U.S. National Seismic Hazard Model periods) as well as the orientation-independent components (e.g., “RotD50”). We refer to ShakeMap products that include these extensions as “extended ShakeMaps.” The added level of complexity motivated us to also develop a user-friendly tool called the “ShakeMap Sampling Tool” (SST) that gives all the estimated shaking metrics for a specific location (or list of locations). Additionally, we develop a web application where users can input locations of interest and view/download the SST results. We further familiarize users with the concept of “Composite ShakeMaps.” For earthquakes sequences such as a mainshock and larger foreshocks and aftershocks, this provides a map of the maximum value of each shaking metric, which is useful for overall loss estimates, the full extent of ground failure triggering potential, and a better portrayal of the repeated shaking levels at a given point for a series of earthquakes. Such a site-specific shaking history facilitates earthquake forensics at building or infrastructure sites for which damage may be of concern, as described in the Disproportionate Damage Earthquake trigger specified in the IEBC (2018, Section 405.2.2) and in developing ATC-145 guidelines (Guidelines for Post-Earthquake Assessment, Repair, and Retrofit of Buildings). The composite ShakeMap can be combined with the SST for a variety of earthquake-hazard applications, such as systematically inferring triggering shaking estimates at specific sites of geotechnical interest for landsliding, liquefaction, and lateral-spreading hazards.

Kahramanmaraş↗
USGS2025

Macroseismology

In this chapter I discuss the use of so-called macroseismic data, i.e., reports of damage and other effects of shaking on humans and the built environment, to improve the characterization of earthquakes and the ground motions they produce. Macroseismic data are critical not only to investigate earthquakes that occurred before the start of the instrumental era in seismology, but are also, by virtue of the spatially rich nature of the data, of tremendous potential importance to investigate early instrumental and even recent earthquakes. Fueled by both the advent of on-line systems that now produce unprecedented volumes of macroseismic intensity data and by recognition of the importance of understanding key historical earthquakes, there has been a growing appreciation for the value of macroseismic data. It is, however, critical to understand both the unique challenges and the unique opportunities associated with these data. I review the evolution of thought and practices regarding analysis of macroseismic data, and the use of such data to improve the characterization of historic and early instrumental earthquakes.

Book chapter↗
USGS2026

Ground-motion aleatory-variability models for Puerto Rico and the U.S. Virgin Islands

I develop independent logic trees for aleatory variability for crustal and subduction-zone (interface and intraslab) earthquakes for seismic hazards analyses in Puerto Rico and the U.S. Virgin Islands (PRVI) from existing suites of ground-motion models (GMMs) and from ground-motion datasets, including a regional PRVI dataset. The aleatory variability models are parameterized using a partially nonergodic partitioning of standard deviation that consists of independently developed between-event ( ), site-to-site ( ), and event-corrected single-station ( ) standard deviation components. The effects of nonlinear site response on aleatory variability are incorporated through additional terms that modify the standard deviation components. Because one goal of this work is to develop independent logic trees for aleatory variability that synthesize the aleatory variability models from GMMs, I make use of the functional forms of the input GMMs. The PRVI dataset contains a limited number of stations with high-quality site metadata and does not contain records from earthquakes with magnitudes greater than 6.1, so I choose not to develop the aleatory variability models from the regional dataset alone. Instead, the standard deviation components from regional ground-motion data are evaluated against the components derived from GMMs and from available global datasets, and regionalized standard deviation components are incorporated where there is evidence that regional effects exhibit substantial differences. The resulting logic trees for aleatory variability consist of models of and that are consistent with semiempirical GMMs for active crustal and subduction-zone regimes, and two alternative models of , including one model that exhibits site-to-site variability informed by PRVI data, with values that exceed global models. The aleatory variability models may be considered in future hazards assessments in PRVI to simplify the hazard calculations, to incorporate regional ground-motion variability effects, and to enable direct logic-tree weighs of aleatory variability.

Puerto Rico, U.S. Virgin Islands↗
USGS2024

A robust quantitative method to distinguish runoff-generated debris flows from floods

Debris flows and floods generated by rainfall runoff occur in rocky mountainous landscapes and burned steeplands. Flow type is commonly identified post-event through interpretation of depositional structures, but these may be poorly preserved or misinterpreted. Prior research indicates that discharge magnitude is commonly amplified in debris flows relative to floods due to volumetric bulking and increased frictional resistance. Here, we use this flow amplification to develop a metric ( Q* ) to separate debris flows from floods based on the ratio of observed peak discharge to the theoretical maximum water discharge from rainfall runoff. We compile 642 observations of floods and debris flows and demonstrate that Q* distinguishes flow type to ∼92% accuracy. Q* allows for accurate identification of debris flows through simple channel cross-section surveys rather than through qualitative interpretation of deposits, and therefore should increase the performance of models and engineered structures that require accurate flow-type observations.

Geophysical Research Letters↗
USGS2025

Persistent deep long-period seismicity near the Lassen Volcanic Center

Deep long-period (DLP) earthquakes have been observed at many volcanic settings around the world and linked to the magmatic processes that drive volcanic unrest. At the Lassen Volcanic Center (LVC) of the Cascade arc, limited detection of DLP activity hinders classification of anomalous seismic behavior and its relationship to the LVC magmatic system. This study uses a template matching approach with seismic data from temporary nodal and permanent stations to detect and locate DLP earthquakes near the LVC between 2017 and 2024. Within the DLP catalog of 611 events, a transition occurs from scattered (2017–2020) to oscillatory (2021–2024) occurrence rates. During the oscillatory period, regional earthquakes with large amplitude velocity waveforms observed near the LVC are associated with abrupt changes in DLP occurrence rates. Continued monitoring of DLP activity has the potential to better define the processes that drive volcanic unrest at the LVC in the future.

California↗
USGS2024

How does the onset of offset influence geologic slip rates?

Geologic slip rates are typically based on the displacement accrued by a geomorphic or stratigraphic feature and the age of the offset feature. Because slip rates are commonly calculated by dividing the displacement of a faulted marker by its age, they contain two open time intervals: the elapsed time between the age of an offset feature and the age of the earthquake that displaced the feature, and the time between the present‐day and the most recent earthquake. Here, we explore the influence of including unconstrained open intervals in geologic slip rate calculations. We test the degree to which these open intervals affect geologic slip rates and their uncertainties, and we find that their influence depends primarily on mean earthquake recurrence intervals (RIs). Slip rates on faults with longer RIs, such as the Wasatch fault, can be greatly influenced by an increase of up to 20% when accounting for open intervals. In contrast, slip rates on faults with shorter RIs, such as the San Andreas fault, are only slightly influenced by the assumption that slip rates calculated over open intervals approximate those calculated over closed intervals. Our analyses indicate that faults with moderate slip rates (∼0.2–5 mm/yr) are sensitive to both open interval effects themselves, as well as methods to quantify and account for these effects. We re‐evaluate how slip rates are calculated and defined in displacement–time space using published deformation records. We explore the utility of assigning a probability distribution to the initiation of offset of the oldest faulted feature and the timing of the most recent earthquake (MRE). We find that calculating geologic slip rates without using probability distributions that capture the timing of the MRE and the onset of offset of the oldest faulted feature, especially on slow‐to‐moderate slip rate faults, can lead to systematic underestimation of average geologic slip rates.

Seismological Research Letters↗
USGS2025

A northeast-dipping zone of low frequency earthquakes at the southern edge of Cascadia subduction

Tectonic tremor monitoring occasionally detects events in an anomalous zone in southern Cascadia, 50–100 km west of the main tremor band, near the expected southern edge of the subducting Gorda slab at the Mendocino triple junction. To investigate the geometry and temporal behavior of this tremor, we examine its constituent low-frequency earthquakes (LFEs) by developing 27 stacked LFE waveform templates that we use to detect events from 2018 to 2024. We then relocate LFE sources together with regional seismicity. We find that LFE hypocenters form a northeast-dipping alignment at 22–29 km depth, extending eastward from a zone of micro-earthquakes, ∼15 km south of the southern edge of Gorda slab seismicity. These LFE families exhibit small bursts of activity every few days. Considering the strong world-wide association of tremor and LFEs with high slip-rate, plate-bounding faults, we hypothesize these LFEs may demark the southern edge of Cascadia subduction.

California↗
USGS2026

Dynamic coupling between faulting, rifting and magmatism during 2021-2025 unrest on Reykjanes Peninsula, Iceland

Interactions among faulting, earthquakes, and eruptions are fundamental to plate tectonics and hazard forecasting yet rarely observed along mid-ocean ridges. On Iceland's Reykjanes Peninsula, seismotectonic–volcanic unrest resumed after nearly 800-year hiatus, providing an opportunity to observe these interactions during 2021–2025 activity. By integrating high-resolution seismicity, focal mechanisms, satellite geodesy, surface deformation, and eruption data, we document ∼4 m of total extension accommodated through 14 rifting episodes. The largest, in 2023, involved graben reactivation and diking, with seismic swarms and earthquake faulting that matched the surface ruptures, where strike-slip faulting preceded normal-faulting earthquakes and extension. The accrued extension was released by extension fractures triggered by magma accumulation. Long-term observations show no correlation between erupted magma volume, seismicity, and crustal extension. This highlights dynamic relation between rifting, faulting, and magmatism in transtensional settings and their implications for hazard assessment.

Reykjanes Peninsula↗
USGS2024

Agricultural return flow dynamics on a reach of the East River, Colorado, as assessed by mass balance

The U.S. Geological Survey, in cooperation with the Upper Gunnison River Water Conservancy District, studied historical streamflow in a reach of the East River, Colorado, to gain a preliminary understanding of return flow dynamics. Return flow is agricultural irrigation water that is not consumed by evapotranspiration and instead reaches streams by surface and subsurface flow paths. The study reach had a contributing area of 50 square miles and contained 5.23 square miles of pastures irrigated with water diverted from the East River and its tributaries. By comparing upstream inflows to downstream outflows, the net water balance of the study reach from 1994 to 2023 was assessed. Two general hydrologic conditions for the study reach were identified. One hydrologic condition was characterized by a net loss or consumption of water, termed here as general deficit. This general deficit condition extended about 16 years, from 1997 to 2012. During general deficit years, there was usually a notable net loss of streamflow from April through July, and a small net gain, possibly related to return flows, occurred in August about 75 days after the minimums for losses. The second hydrologic condition was characterized by a net gain of water, termed here as general surplus. This second condition extended about 10 years, from 2014 to 2023. During general surplus years, two separate transitions from net loss to net gain commonly occurred during June through August. Losses during general surplus years were smaller than losses during general deficit years, the respective gains were larger, and times between losses and gains were about 18 and 22 days. Differences between the two hydrologic conditions could reflect interactions among irrigation water, available capacity to store additional shallow groundwater, and streamflow. However, deciphering the causes for the shifts between the two general hydrologic conditions was beyond the scope of this report.

Colorado↗
USGS2025

Modeling seawater intrusion along the Alabama coastline using physical and machine learning models to evaluate the effects of multiscale natural and anthropogenic stresses

Seawater intrusion threatens groundwater resources in coastal regions, including southern Baldwin County, Alabama, where the freshwater-saltwater interface dynamics remain poorly understood. To address this gap, this study uses combined physics-based and machine-learning models to quantify seawater intrusion caused by natural (storm surges) and anthropogenic (human activities) perturbations. The long short-term memory network and wavelet analysis were used to assess vertical aquifer vulnerabilities, revealing that the shallow part of the Coastal lowlands aquifer system (CL1) in the southern Baldwin County region is more susceptible to sea level rise and groundwater extraction than deeper aquifers. Based on these findings, a cross-sectional numerical model (physics approach) for the CL1 aquifer was developed to evaluate tidal and storm surge effects, using Tropical Storm Claudette (June 2021) as a case study. Results showed that tidal fluctuations had a minimal impact on the saltwater-freshwater interface location, whereas storm surges caused substantial inland movement, with effects lasting for nine months. The steady-state version of the three-dimensional (3D) physical model predicted seawater intrusion across the entire area, and convolutional neural network-based modeling further validated the model results. The 3D physical model was also applied to a smaller area to assess human impact on the saltwater interface due to two groundwater pumping scenarios (± 50% of the baseline pumping rate). Results revealed that a 50% increase in groundwater withdrawals caused seawater to advance ~ 320 m inland, whereas a 50% reduction led to a ~ 270-meter retreat. This study highlights the vulnerability of Alabama’s shallow coastal aquifers to seawater intrusion due to storm surges and human activities, and demonstrates that combining physics-based models with machine learning approaches can improve groundwater predictions, though its accuracy depends on the availability of site-specific data.

Alabama↗
USGS2025

SURF: An automated method for building nonplanar 3D fault models from earthquake hypocenters

Accurately characterizing 3D fault geometry is vital for improving our understanding of earthquake behavior and informing the development of seismic hazard models. Despite their importance, subsurface fault structures tend to be poorly constrained because of limitations in observational data. Improvements to the seismic networks and earthquake detection algorithms have increased the precision and volume of earthquake catalogs, which help illuminate detailed subsurface fault structure and provide the most direct information available about fault geometries at depth. We present a Python package to automate generating 3D fault geometries directly from hypocentral seismicity patterns. This method begins with clustering events based on their spatial density, identifying coherent patterns. Nearby clusters are then merged based on the similarity of their orientations. We fit nonplanar surfaces using support vector regression to balance surface accuracy with minimal deviations from planarity. The fault models are output as quadrilateral meshes at user‐defined resolution. In the process of generating the 3D fault surfaces, we compute the spatial density of seismicity around the surface and the planarity as quantitative metrics of the model outputs. As a proof of concept, we apply this approach to the San Andreas–Calaveras fault junction region and the 2019 Ridgecrest earthquake sequence, both in California, which contain complex subparallel faults well defined at the Earth’s surface and abundant microseismicity. These case studies demonstrate the method’s ability to model complex fault structures, including long continuous fault surfaces, crossing faults, variably dipping segments, and subparallel faults. We test the method on both standard network catalogs and double‐difference relocated catalogs. We find that our seismicity‐based fault model results align with published 3D models that incorporate additional constraints and interpretations ( Plesch et al. , 2020 ; Aagaard and Hirakawa, 2021 ). This workflow provides a low‐user‐input solution for estimating fault geometries at depth from earthquake catalogs.

California↗
USGS2024

3-D mapping of the conterminous U.S. within the USGS National Cooperative Geologic Mapping Program: Progress and future prospects

The U.S. Geological Survey (USGS) National Cooperative Mapping Program (NCGMP) is bringing together subsurface and three-dimensional information at multiple scales for the conterminous United States from data produced throughout the USGS and by federal and state partners. Components of this work include data inventory and catalog development, data integration and database development, and construction of subregional and basin-scale three-dimensional (3-D) geologic models. At small scales, the NCGMP is compiling subsurface data to create a limited number of subsurface layers that map the majority of the lower 48 States. At larger scales, 3-D models of stratigraphic units are intended to be the subsurface analog and extension of the surface geologic maps made within the Program. The Mapping Program is developing methods of storing, visualizing, and distributing 3-D models and subsurface data from multiple sources in easily shareable, queryable, non-proprietary format(s). We report on progress in 3-D mapping of the conterminous U.S. and on future prospects.

conterminous United States↗
USGS2024

Hypothetical CO2 leakage into, and hydrological plume management within, an underground source of drinking water at a proposed CO2 storage facility, Kemper County, Mississippi, USA

A large Geologic Carbon Sequestration (GCS) hub has been proposed in Kemper County, Mississippi. The target injection interval consists of numerous Cretaceous-aged deep saline aquifers overlain by a competent and extensive regional sealing layer. Above the seal, the deepest Underground Source of Drinking Water (USDW) at the site is the Eutaw aquifer of the Eutaw Group and McShan Formation, undifferentiated. To assess potential risks of leakage from the deep sequestration reservoir, a model of a portion of the Cretaceous Eutaw Group was constructed in this study. Simulations tested various permeabilities, hypothetical leakage rates, and plume mitigation strategies utilizing existing wells. Results suggest that, under the influence of regional groundwater flow fields, leaking CO 2 would effectively bypass the existing wells, and to influence this migration would require very large water extraction rates. Therefore, to ensure plume detection, monitoring for leakage at the injection wells themselves is very important.

Mississippi↗
USGS2026

Temperate wetlands lose climate-cooling capacity under warming

Temperate inland wetlands have long been viewed as climate regulators, with sustained CO₂ sequestration offsetting continuous CH₄ emissions over centennial–millennial timescales. However, the net climatic effect of these opposing fluxes remains uncertain under anthropogenic warming as they differ in both magnitude and atmospheric lifetime. We combine 19,000 CH₄ chamber measurements from 202 temperate inland wetlands with carbon burial rates from 16 dated sediment cores in North America’s Prairie Pothole Region to estimate greenhouse gas dynamics over two centuries. Here we show that CH₄ emissions rise by ~1.39 kg CH₄ ha⁻¹ yr⁻¹ over the historical period and are projected to approach 950 kg CH₄ ha⁻¹ yr⁻¹ under high-forcing scenarios by 2100, while CO₂ sequestration is expected to decline by ~0.3 kg CO₂ ha⁻¹ yr⁻¹, driving a shift toward persistent net CO₂-equivalent source behaviour and a weakening of the long-term cooling effect that wetlands have provided under natural conditions.

Prairie Pothole Region↗
USGS2025

Combining multisite tsunami and deformation modeling to constrain slip distributions for the 1700 C.E. Cascadia earthquake

A major earthquake ruptured the Cascadia subduction zone (CSZ) on 26 January 1700. Key paleoseismic evidence associated with this event include tsunami deposits, stratigraphic evidence of coastal coseismic subsidence, written Japanese records of a tsunami unaccompanied by earthquake shaking, and margin‐wide turbidites found offshore and in lacustrine environments. Despite this wealth of independent clues, important details about this event remain unresolved. Dating uncertainties do not conclusively establish whether the proxies are from one earthquake or a sequence of them, and we have limited knowledge of the likely slip distributions of the event or events. Here, we use a catalog of 37,500 candidate synthetic ruptures between M w 7.8 and 9.2 and simulate their resulting coseismic deformation and tsunami inundation. Each model is then compared against estimated Japan tsunami arrivals, regional coastal subsidence records, and local paleotsunami deposits mapped at six different coastal marshes and one coastal lake along the CSZ. We find that seven full‐margin ruptures with a median magnitude of M w 9.1 satisfy all three constraints. We favor one M w 9.11 model that best matches all site paleoseismic observations and suggests that the Cascadia megathrust slipped up to ∼30 m and must have shallow geodetic coupling. We also find that some sequences composed of three or four ruptures can still satisfy the observations, yet no sequences of two ruptures can. Sequences are differentiated into three groups based on whether they contain a mainshock rupture located in the south (>44° N) or further north. All sequences contain unruptured portions of the megathrust and most contain mainshocks with peak slip above 40 m. The fit of the geologic evidence from sequences is poor in comparison to single‐event models. Therefore, sequences are generally less favored compared to full‐margin events.

British Columbia, California, Oregon, Washington↗
USGS2026

Regional models for postfire debris-flow likelihood and rainfall thresholds across the western United States

The U.S. Geological Survey (USGS) uses an empirical model developed with logistic regression (the ‘M1’ model) to rapidly assess debris-flow likelihood and to identify quantitative rainfall thresholds for debris flows after wildfire in the western United States. The M1 model was calibrated to a debris-flow inventory from southern California (United States) and has been applied throughout the western United States. Limited spatial coverage in the calibration dataset has motivated evaluation of M1 model accuracy outside the calibration region (e.g., the Sierra Nevada or the eastern Cascade Range, United States). Previous test cases showed that M1 overpredicts debris-flow likelihood and underpredicts rainfall thresholds for some locations (e.g., Arizona, northern California, Colorado, New Mexico, United States). We sought to improve the regional applicability of a debris-flow likelihood model by expanding the debris-flow inventory used for calibration, testing multiple potential models and generating an updated model framework. The updated inventory includes 3788 observations from 67 burned areas paired with short duration rainfall ratios. The updated model framework consists of a modified model structure and sets of coefficients calibrated separately to the entire updated inventory and to subsets of the inventory that intersect three Environmental Protection Agency (EPA) Level 2 ecoregions (Mediterranean California, Upper Gila Mountains and Western Cordillera). Comparisons of predictions from the updated models with observed rainfall and debris-flow activity show that the updated models outperform the M1 model by ~15%–60% and improve the uniformity of predictive performance across the western United States. The updated models also reduce false positive rates relative to M1 and generate rainfall thresholds that are better aligned with relative differences in regional climatology and debris-flow activity.

Arizona, California, Colorado, Idaho, Montana, Nev↗